# Mathematical Statistics with Resampling and R

John Wiley & Sons, Sep 17, 2018 - Mathematics - 560 pages

This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques

Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The second edition of Mathematical Statistics with Resampling and R combines modern resampling techniques and mathematical statistics. This book has been classroom-tested to ensure an accessible presentation, uses the powerful and flexible computer language R for data analysis and explores the benefits of modern resampling techniques.

This book offers an introduction to permutation tests and bootstrap methods that can serve to motivate classical inference methods. The book strikes a balance between theory, computing, and applications, and the new edition explores additional topics including consulting, paired t test, ANOVA and Google Interview Questions. Throughout the book, new and updated case studies are included representing a diverse range of subjects such as flight delays, birth weights of babies, and telephone company repair times. These illustrate the relevance of the real-world applications of the material. This new edition:

• Puts the focus on statistical consulting that emphasizes giving a client an understanding of data and goes beyond typical expectations

• Presents new material on topics such as the paired t test, Fisher's Exact Test and the EM algorithm

• Offers a new section on "Google Interview Questions" that illustrates statistical thinking

• Provides a new chapter on ANOVA

• Contains more exercises and updated case studies, data sets, and R code

Written for undergraduate students in a mathematical statistics course as well as practitioners and researchers, the second edition of Mathematical Statistics with Resampling and R presents a revised and updated guide for applying the most current resampling techniques to mathematical statistics.

### Contents

 Chapter 1 Data and Case Studies 1 Chapter 2 Exploratory Data Analysis 21 Permutation Tests 47 Chapter 4 Sampling Distributions 75 The Bootstrap 103 Chapter 6 Estimation 149 Chapter 7 More Confidence Intervals 187 Chapter 8 More Hypothesis Testing 241
 Chapter 12 Oneway ANOVA 419 Chapter 13 Additional Topics 433 Appendix A Review of Probability 477 Appendix B Probability Distributions 487 Appendix C Distributions Quick Reference 509 Solutions to Selected Exercises 513 References 525 Index 531

 Chapter 9 Regression 297 Chapter 10 Categorical Data 359 Chapter 11 Bayesian Methods 391